Many diseases (including heart disease, diabetes, cancer, and neurological disorders such as Parkinson's disease) cannot be understood in terms of single-cause/single-effect relationships. This is because although there exist both a depth of knowledge of basic physiology and a host of physiological and genomic data from animal models of disease, we lack an understanding of how multiple genes and environmental factors interact to determine phenotype. We propose to revolutionize our understanding of complex phenotypes and diseases based on systematic multi-scale measurement, simulation, and analysis of physiological function in the rat. Specifically, we propose to initiate The Virtual Physiological Rat Project to develop computational tools to capture the underlying systems physiology as well as the pathophysiological perturbations associated with disease. These tools will be developed and validated based on experimental characterization of physiological function across a number of organ systems in rat strains engineered to show relevant disease phenotypes. Computer simulation will be used to integrate disparate data (genomic, anatomic, physiological, etc.) to explain and predict function, and to translate the findings from animal models to yield new information on specific interrelated complex diseases in humans, including hypertension, kidney disease, heart failure, and metabolic syndrome. The developed multi-scale physiological models will be linked to genotype- phenotype parametric maps to construct a Virtual Physiological Rat resource, which will be used to predict the influence of genetic variability and environmental factors on phenotypes and to predict phenotypes of new strains that will be experimentally derived and characterized. By systematically and iteratively using multi-scale computational models to analyze data, generate hypotheses, design experiments, and predict phenotypes in novel strains of rat, we will attain the capability to predict and understand the emergence of complex traits. In addition to the direct impact of the proposed scientific studies, the VPR Center will be a resource to the broader community by delivering unique software and associated data for cardiovascular systems research. In addition, we will develop courses, workshops, and related educational material, train and recruit scientists from underserved communities, and hold annual scientific meetings for affiliated and nonaffiliated investigators.

Public Health Relevance

Despite a depth of knowledge of basic cardiovascular physiology, we lack even a rudimentary understanding of how multiple genes and environmental factors interact to determine cardiovascular phenotype. This proposal targets the grand challenge of understanding complex multi-faceted disease phenotypes through experiments and simulations that capture the complex genotype-environment-phenotype relationship.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Specialized Center (P50)
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Special Emphasis Panel (ZGM1-CBCB-2 (SB))
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Brazhnik, Paul
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Medical College of Wisconsin
Schools of Medicine
United States
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Herum, Kate M; Choppe, Jonas; Kumar, Aditya et al. (2017) Mechanical regulation of cardiac fibroblast profibrotic phenotypes. Mol Biol Cell 28:1871-1882
McClymont, Darryl; Teh, Irvin; Carruth, Eric et al. (2017) Evaluation of non-Gaussian diffusion in cardiac MRI. Magn Reson Med 78:1174-1186
Sturdy, Jacob; Ottesen, Johnny T; Olufsen, Mette S (2017) Modeling the differentiation of A- and C-type baroreceptor firing patterns. J Comput Neurosci 42:11-30
Cooling, Michael T; Nickerson, David P; Nielsen, Poul M F et al. (2016) Modular modelling with Physiome standards. J Physiol 594:6817-6831
Gattoni, Sara; Røe, Åsmund Treu; Frisk, Michael et al. (2016) The calcium-frequency response in the rat ventricular myocyte: an experimental and modelling study. J Physiol 594:4193-224
Dewan, Sukriti; McCabe, Kimberly J; Regnier, Michael et al. (2016) Molecular Effects of cTnC DCM Mutations on Calcium Sensitivity and Myofilament Activation-An Integrated Multiscale Modeling Study. J Phys Chem B 120:8264-75
Yipintsoi, Tada; Kroll, Keith; Bassingthwaighte, James B (2016) Fractal regional myocardial blood flows pattern according to metabolism, not vascular anatomy. Am J Physiol Heart Circ Physiol 310:H351-64
Tewari, Shivendra G; Gottipati, Manoj K; Parpura, Vladimir (2016) Mathematical Modeling in Neuroscience: Neuronal Activity and Its Modulation by Astrocytes. Front Integr Neurosci 10:3
Neal, Maxwell L; Gennari, John H; Cook, Daniel L (2016) Qualitative causal analyses of biosimulation models. CEUR Workshop Proc 1747:
Tewari, Shivendra G; Bugenhagen, Scott M; Palmer, Bradley M et al. (2016) Dynamics of cross-bridge cycling, ATP hydrolysis, force generation, and deformation in cardiac muscle. J Mol Cell Cardiol 96:11-25

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